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Tem

Staff Product Manager - Rosso

United KingdomRemote · United Kingdom
Staff · FullTime · Product
POSTED 6 NOVVERIFIED 1D AGO
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Role
7 days opentrue age
Posted 6 Nov
Payats field
£128kposted
▼ −1% vs market median £129k
£119k£131k
Market p25–p75
£119k–£131k
United Kingdom · n=8 · 365d to 10 Nov
CompanyTem →
24open roles
Opened · 30d
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Closed · 30d
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738open · Staff Product
Opened · 7d
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8,076open
All tracked boards · live 14 Nov · n=738
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📈 Who We Are

We are rebuilding the energy transaction, making it transparent and fair.

We're rebuilding how energy is bought and sold. That means cutting out middlemen, connecting businesses directly with renewable generators, and ensuring every transaction is traceable and transparent.

We're a 160+ person team - operators, data scientists, engineers, customer champions and energy experts - backed by top-tier investors including Lightspeed Venture Partners, Hitachi Ventures, Allianz, AlbionVC and Atomico. We closed a $75M Series B round in early 2026, taking our total funding to $94M, and we now power energy for over 4,000 UK businesses across 8,500+ sites, with over £75m in value returned to businesses and generators so far.

We're a technology company solving the energy industry, not an energy company. Some people call us a neo-utility, the neo-bank idea, applied to energy.

The industry is noticing. We were crowned Europe's Most Exciting Tech Company at the GP Bullhound Allstars awards, came in at #6 on LinkedIn's Top Startups 2026 in the UK, #7 on the Scaling Europe 50 of Europe's fastest-growing companies, and #14 on Sifted's AI 100.

Learn more about us on our website.

The Role

We’re hiring a Staff Product Manager to own the portfolio side of Rosso, a hands-on role built around financial outcomes.

Rosso is deeply technical, built on ML-led models and complex engineering covering forecasting, pricing optimisation and portfolio balancing. The portfolio is where the live financial risk sits: fulfilling and balancing a growing two-sided portfolio, managing imbalance, controlling portfolio costs, and finding the revenue and margin in every position we hold. It’s still forming, and it needs someone who wants to own the outcome and win in it.

This is a lead role, but not a head-of-product role. You’ll be building, not running a product practice. You’ll work day to day with engineers and ML specialists to build an automated portfolio management system that handles balancing, forecasting and counterparty placement, and that could be exposed to third parties in future.

You will

Own financial outcomes for the portfolio, including the cost of balancing and managing positions, and be accountable for margin found and risk managed.

Work hands-on with engineers and ML/data science to build automated, quantitative systems that run at scale and under live financial risk.

Drive open product decisions to a close, with a clear Now, Next and Future for the portfolio area.

🚀 Responsibilities

Own the portfolio outcome

Take full ownership of financial outcomes in the portfolio area: balancing, imbalance, forecasting and counterparty placement.

Treat hedging, imbalance and trading decisions as product decisions: when to hold a position, when to trade it out, when to reprice to close a gap.

Find the most pressing problems worth solving, such as whether to buy or build a new forecasting capability, or how to make Rosso react at scale to any event in the system.

Chase the commercial outcome, not just the shipped feature. The measure of this role is margin found and risk managed, at pace.

Turn needs into shipped product

Take business and customer needs and turn them into feasible product execution, balancing them against nascent ML and forecasting innovations that push the frontier of what’s possible.

Take initiatives from discovery through to regularly released product.

Drive open product decisions to a close, yours and the team’s, so work keeps moving.

Decide what to formalise, what stays a prototype and what to drop. Be the editor and builder, not just the instigator.

Own the technical-product detail

Work embedded in full-stack teams of ML/data science and software engineers, close enough to the systems to make good calls.

Set clear success criteria for how well a model or forecast needs to perform for the product to work, and design for the edge cases and operational reality of a system carrying live financial risk.

Pull and interrogate your own and others’ data to inform decisions, and reason about model performance and error as business indicators.

Source · TemFirst seen 7 Nov1 editsOriginal ↗